Author

R. A. Syunyaev

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2 Physiology· 1

Signature Assays, Organisms & Methods

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Assay:electrophysiology· 3 Organism:human· 3 Research Focus:cell type annotation· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:biophysical modeling· 1 Research Focus:differential expression· 1 Approach:genetic perturbation / CRISPR· 1

Frequent Co-Authors

I. R. Efimov· 3 shared A. V. Pikunov· 2 shared I. Kutschka· 2 shared N. Voigt· 2 shared V. Steckmeister· 2 shared A. C. Koppel· 1 shared A. Prakosa· 1 shared D. N. Smirnov· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersBiophysics

I. R. Efimov

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Author profile →

3 papers

Recent·Most cited

The role of structural vs cellular remodeling in arrhythmogenesis: personalized computer models of atrial fibrillation.

A. V. Pikunov, R. A. Syunyaev, R. Ali, A. Prakosa, P. M. Boyle, V. Steckmeister, I. Kutschka, E. Rytkin, N. Voigt, N. Trayanova, I. R. Efimov

This study uses personalized computer models to analyze how structural and cellular changes contribute to atrial fibrillation, showing that electrophysiological remodeling influences arrhythmogenic substrate and driver locations.

bioRxiv · May 13, 2023 · PreprintPhysiology

Personalization of mathematical models of human atrial action potential

A. V. Pikunov, R. A. Syunyaev, V. Steckmeister, I. Kutschka, N. Voigt, I. R. Efimov

The paper benchmarks two electrophysiological models of human atrial myocytes using genetic algorithm fitting of patch-clamp data, showing Maleckar model better captures heart rate dependence of APD and RP.

bioRxiv · Jun 29, 2020 · PreprintBiophysics

Genetic algorithm-based personalized models of human cardiac action potential

D. N. Smirnov, R. A. Syunyaev, R. M. Deviatiiarov, O. A. Gusev, K. K. Aras, A. C. Koppel, I. R. Efimov

The paper develops a genetic algorithm to personalize cardiac action potential models using experimental data, achieving low error in waveform and duration predictions.

bioRxiv · Jul 23, 2019Biophysics